Manipulation of Polymorphic Objects Using Two Robotic Arms through CNN Networks
作者: Robinson JimenezAndres JimenezJohn Anzola
刊名: International Journal on Advanced Science, Engineering and Information Technology, 2019, Vol.9 (4), pp.1086-1095
来源数据库: Indonesian Society for Knowledge and Human Development
DOI: 10.18517/ijaseit.9.4.7794
关键词: Robotic armsR-CNNDAG-CNN3-finger gripperPolymorphic objectsGrip detectionRobot interaction.
原始语种摘要: This article presents an interaction system for two 5 DOF (Degrees of Freedom) manipulators with 3-finger grippers, which will be used to grab and displace up to 10 polymorphic objects shaped as pentominoes, inside a VRML (Virtual Reality Modeling Language) environment, by performing element detection and classification using an R-CNN (Region Proposal Convolutional Neural Network), and point detection and gripping orientation using a DAG-CNN (Directed Acyclic Graph-Convolutional Neural Network). It was analyzed the feasibility or not of a grasp is determined depending on how the geometry of an element fits the free space between the gripper fingers. A database was created to be used as training data with each of the grasp positions for the polyshapes, so the network training can be...
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  • gripper 抓取装置
  • manipulator 控制器机械手
  • rotation 旋转
  • grasp 抓住
  • shape 形状
  • Robot 罗伯特牌照相机
  • passing 通过的
  • training 培养
  • database 资料库
  • DOF Degrees Of Freedom